Surface Emissivity Research Articles

Surface activation of n-type AlGaN with cesium and oxygen to enhance thermionic emission

The aim of this study is to enhance the characteristics of thermionic emission of AlGaN surface through surface control employing cesium (Cs) and oxygen. Cs-deposited AlGaN has significant applications in thermionic energy converters. However, as the emitter temperature increases, the thermal desorption of Cs from AlGaN surface increases, resulting in a decrease in the thermionic emission current. Therefore, focusing on the high affinity between Cs and oxygen, we investigated the possibility of suppressing thermal desorption by depositing Cs and oxygen on AlGaN surface. The thermionic emission current measured when Cs and oxygen were alternately deposited on AlGaN surface was 1.9 × 10−3 A cm−2 at 500 °C. The thermionic emission current was significantly higher than that obtained with Cs-only deposition (2.0 × 10−5 A cm−2). In addition, we attempted to reproduce the effect of dynamic surface changes on thermionic emission employing a new thermionic emission model (modified Richardson–Dushman model) that considers the correlation between a specific surface reconstruction phase and its thermionic emission component. The results suggest that the adsorbed component of Cs-deposited AlGaN exhibits three Cs adsorption sites with different desorption energies, while the adsorbed component of Cs/O2 co-deposited AlGaN exhibits at least four Cs adsorption sites with different desorption energies. It is suggested that the increase in adsorption components with higher desorption energies, caused by the deposition of oxygen, may have reduced the thermal desorption and improved Cs coverage and stability.

Repetitively pulsed streamer discharge with laser-induced surface trapped electron desorption to exploit residual charges in situ

Positive streamer behaviors under repetitive pulses are predominantly dependent on the availability of free electrons. If surface residual electrons stored from previous discharges could be intentionally released and involved into the next discharge, an alternative control freedom is provided apart from voltage waveform tailoring methods that mainly attract or repel gaseous residual charges. Evolutions of repetitively pulsed surface streamers in compressed (0.2 MPa) air were investigated after low-photon-energy pulsed visible (532 nm) and infrared (1064 nm) laser irradiations. Pulse-sequence and temporally resolved diagnostics were implemented to investigate effects of laser parameters (irradiation moment, wavelength, energy) and gas composition. A 2D surface streamer fluid simulation was performed to qualitatively unveil impacts of localized plasma patches. The surface streamer morphology and emission light are significantly and repeatably affected by the laser irradiation before the streamer inception, while, variations totally disappear without the solid surface. The secondary streamer is prolonged accompanied by a higher flashover probability after the pulsed laser irradiation in compressed air. Intriguingly, influences of the infrared laser persist for tens of microseconds before the next voltage pulse. Residual charge dynamics under the laser irradiation are analyzed, where the additional increase of O2− of low electron bound energy is emphasized. The laser induced surface trapped electron desorption is achieved through the direct or the step-wise process, dependent on the laser energy and the surface trap state distribution.

Monitoring Land Surface Temperature Trends in Indonesia

Monitoring Land Surface Temperature (LST) trends helps identify provinces vulnerable to temperature changes and aids in developing appropriate adaptation and mitigation strategies. This research article aims to monitor LST trends in Indonesia from 2000 to 2022 using MODIS Aqua Land Surface Temperature and Emissivity (MYD11A1) imageries. The study utilizes LST Day and LST Night datasets obtained from MYD11A1 datasets to achieve its research objective. Sens’ Slope is employed to identify and measure the magnitude and direction of temperature changes, while the Mann-Kendall trend test detects significant LST trends. GEE is used to process and analyze MODIS LST data. The findings show a significant increase in LST Night during the June-August (JJA) period in most provinces of Indonesia. LST Day data also stresses that some provinces in Indonesia are experiencing a warming trend. Elevation and population increases may contribute to the observed increasing LST trend. Notably, a short-term decrease in LST may occur within the long-term increasing LST trend.

Assessment of daytime and nighttime surface urban heat islands across local climate zones – A case study in Florianópolis, Brazil

Affected air movement, artificial heat production, increased solar absorption and suppressed vegetation cause significant temperature differences between urban and suburban/rural regions, forming Surface Urban Heat Islands (SUHI). Here, we propose a methodological framework combining daytime and nighttime Landsat 8 data with comprehensive statistical evaluation based on the retrieved information. To quantify SUHI, we selected a pair of daytime and nighttime Landsat 8 scenes, calculated the Urban Thermal Field Variance Index and applied a comprehensive statistical approach to assess differences in SUHI behaviour across Local Climate Zones and between day and night, examining its relationships with albedo, elevation, land surface emissivity and vegetation cover. Open urban typologies were characterised by milder day temperatures, especially over open areas with higher buildings, while compact low-rise areas presented the highest SUHI intensity. Higher buildings presented more intense SUHI at night, with milder temperatures over open and low-rise regions. These results confirm the SUHI dynamics and its strong association with the urban structure and the presence of vegetation. The proposed complex methodological framework can be, with minor adjustments, applied to other regions as well, which can improve the comparability among studies on SUHI and promote our understanding of its causes and possible mitigation measures.

Alternative coatings to cyanide silver coatings with low infrared emissivity for tokamak components

Alternative to cyanide silver coatings with low infrared emissivity for tokamak components were prepared by cyanide-free silver plating on nuclear-grade 304L stainless steel. The surface morphology, coating adhesion and emissivity were characterized and optimized. The experimental results indicate that the developed cyanide-free silver coating is a viable alternative to cyanide silver coating. The adhesion of silver coating was enhanced by the reactivating of nickel plating. The emissivity was reduced by decreasing surface roughness and increasing coating thickness. Both optimizations reach limit at 0.4 μm and 0.6 μm, respectively. Further decrease in surface roughness and increase in coating thickness did not contribute to decreasing emissivity. To sum up, the obtained cyanide-free silver coatings showed sufficient adhesion with emissivity as low as 0.02, thus providing an eco-friendly alternative solution to fusion energy application.

Satellite Time-Series Analysis for Thermal Anomaly Detection in the Naples Urban Area, Italy

Naples is the most densely populated Italian city (7744 inhabitants per km2). It is located in a particular geological context: the presence of Mt Vesuvius characterizes the eastern part, and the western part is characterized by the presence of the Phlegrean Fields, making Naples a high-geothermal-gradient region. This endogenous heat, combined with the anthropogenic heat due to intense urbanization, has defined Naples as an ideal location for Surface Urban Heat Island (SUHI) analysis. SUHI analysis was effectuated by acquiring the Land Surface Temperature (LST) over Naples municipality by processing Landsat 8 (L8) Thermal Infrared Sensor (TIRS) images in the 2013–2023 time series by employing Google Earth Engine (GEE). In GEE, two different approaches have been followed to analyze thermal images, starting from the Statistical Mono Window (SMW) algorithm, which computes the LST based on the brightness temperature (Tb), the emissivity value, and the atmospheric correction coefficients. The first one is used for the LST retrieval from daytime images; here, the emissivity component is derived using, firstly, the Normalized Difference Vegetation Index (NDVI) and then the Vegetation Cover Method (VCM), defining the Land Surface Emissivity (LSɛ), which considers solar radiation as the main source of energy. The second approach is used for the LST retrieval from nighttime images, where the emissivity is directly estimated from the Advance Spaceborne Thermal Emission Radiometer database (ASTER-GED), as, during nighttime without solar radiation, the main source of energy is the energy emitted by the Earth’s surface. From these two different algorithms, 123 usable daytime and nighttime LST images were downloaded from GEE and analyzed in Quantum GIS (QGIS). The results show that the SUHI is more concentrated in the eastern part, characterized by intense urbanization, as shown by the Corine Land Cover (CLC). At the same time, lower SUHI intensity is detected in the western part, defined by the Land Cover (LC) vegetated class. Also, in the analysis, we highlighted 40 spots (10 hotspots and 10 coldspots, both for daytime and nighttime collection) that present positive or negative temperature peaks for all the time series. Due to the huge amount of data, this work considered only the five representative spots that were most representative for SUHI analysis and determination of thermal anomalies in the urban environment.

Validation of Remotely Sensed Land Surface Temperature at Lake Baikal’s Surroundings Using In Situ Observations

The accuracy of Land Surface Temperature (LST) products retrieved from satellite data in mountainous-coastal areas is not well understood. This study presents an analysis of the spatial and temporal variability of the differences between the LST and in situ observed air and surface temperatures (ISTs) for the southeastern slope of Lake Baikal’s surroundings. The IST was measured at 12 ground observation sites located on the southeastern macro-slope of the Primorskiy Ridge (Baikal, Russia) within an elevation range of 460–1656 m above sea level from 2009 to 2021. LST was estimated using 617 Landsat (7 and 8) images from 2009–2021, taking into account brightness temperature, surface emissivity and vegetation cover fraction. The comparison of the LST from satellite data and the IST from ground observation showed relatively high differences, which varied depending on the season and site type. A neural network was suggested and calibrated to improve the LST data. The corrected remote-sensed temperature was found to reproduce the IST very well, with mean differences of about 0.03 °C and linear correlation coefficients of 0.98 and 0.95 for the air and surface IST.

A computational model of an air-layer radiant cooling panel for optimizing and design

Radiant cooling systems have become a research hotspot in recent years. The air-layer radiant cooling panel always had good performance, but there is relatively little research on it. This paper aims to optimize an air-layer radiant cooling panel by establishing a computational model and analyzing its accuracy through experiments. Through the computational model, the effects of surface emissivity, the thickness of the air layer and high thermal resistance material, pipe spacing on the heat transfer performance of the air-layer radiating cooling panel, and the corresponding optimizations have been studied in this paper. Based on the results, it is recommended that a pipe spacing of between 0.1 m and 0.25 m can achieve higher cooling capacity and lower initial costs. The thinner the thickness of the air layer and decorative layer, the better the heat transfer performance. High emissivity materials need to be used on the surface of the air-layer radiant cooling panel to enhance radiant heat transfer. In the process of analyzing the spacing between pipes, a method for calculating the large temperature difference of the fluid has been added, which can help us estimate the cooling capacity in practical engineering, balance initial costs and cooling capacity, and better meet cooling needs.

Correcting land surface temperature from thermal imager by considering heterogeneous emissivity

It is fundamental to obtain accurate land surface temperature (LST) to study surface energy process. Infrared thermal imagers are commonly used for deriving LST on the basis of radiance measurements. However, when deriving LST from brightness temperature of a blackbody in thermal imagers, thermal imagers only allow setting a fixed land surface emissivity (LSE). This causes uncertainty in retrieving thermal infrared (TIR) temperature from heterogeneous surfaces with varied LSE, such as those covered in vegetation. Corrections can be made using the Normalized Vegetation Index (NDVI). However, commercial thermal imagers provide only red (R), green (G), and blue (B) bands without a near infrared band so NDVI cannot be calculated on the same instrument and is commonly not available. We propose an alternative method to estimate LSE using RGB-based vegetation index. Thereafter the estimated LSE was used to correct the TIR temperature derived from the fixed LSE. An experiment was conducted to validate the proposed correcting method. The results show that 1) the corrected LST values were closer to the ground truth, with a mean absolute error (MAE) of 0.41 ± 0.34 °C, whereas the MAE was 0.75 ± 0.56 °C for the uncorrected LST; 2) the more heterogeneous the surface, the greater the difference between the corrected and uncorrected LST values, indicating the necessity of LST correction when applying thermal imagers over heterogeneous surface.

Research on Landsat 8 land surface temperature retrieval and spatial–temporal migration capabilities based on random forest model

Land surface temperature (LST) plays a crucial role in characterizing land surface processes and the energy balance. Accurate monitoring of spatial–temporal variations in LST holds great significance for global and regional climate change research. However, with the increasing of multi-source remote sensing data, it has become a challenging task to construct an LST model that reduces dependence on auxiliary data (such as land surface emissivity (LSE) and atmospheric water vapor content (WVC) synchronized with satellite observations. This study proposed an LST retrieval model based on random forest model (RFLSTR). The results of 10-fold cross-validation showed that the RFLSTR model had high modelling accuracy, the root mean square error (RMSE) and mean absolute error (MAE) were lower than 2 K. Landsat 8 images from the Beijing area and South Korea, were utilized to assess the spatial–temporal migration performance of the RFLSTR model. Additionally, Landsat 9 images from South Korea were employed to analyse the sensor migration performance of the RFLSTR model. In conclusion, the findings highlight that the proposed RFLSTR model achieve high retrieval accuracy without relying on auxiliary data (such as LSE and WVC) synchronized with satellite observations. Moreover, the RFLSTR model exhibits robust spatial–temporal capabilities, enhancing the efficiency of LST retrieval and facilitating the utilization of satellite data.

Quantum Cascade Surface Emitting Lasers

AbstractA low‐cost single frequency laser, emitting in the mid‐infrared spectral region and dissipating minimal electrical power, is a key ingredient for the next generation of portable gas sensors for high‐volume applications involving chemical sensing of important greenhouse and pollutant gases. Herein, a Quantum Cascade Surface Emitting Laser (QCSEL) is proposed, which is implemented as a short linear cavity with high reflectivity coated end‐mirrors to suppress any edge emission and employs a buried semiconductor diffraction grating to extract the light from the surface. By wafer‐level testing, the cavity length scaling is investigated, mirror reflectivities larger than 0.9 are extracted, and a pulsed threshold power dissipation of 237 mW for an emission wavelength near 7.5 µm is achieved. Finally, single‐mode emission with a side‐mode suppression ratio larger than 33 dB is demonstrated for a 248 µm short cavity, which is mounted with the epitaxial layer up and operated in continuous wave at 20 .

Quantitative risk assessment of a spill fire caused by the continuously leaked fuel in a sealed ship engine room

There are a large number of high-temperature heat sources in a ship engine room. Once the oil leakage occurs, it is likely to be ignited and form a spreading and burning spill fire. In this paper, spill fire experiments are conducted in a model-scale ship engine room to investigate their characteristic parameters. The quantitative models of flame height and thermal radiant surface emission power applicable to such fires are verified by the experimental data. Based on that, the classical quantitative risk assessment method is adopted to assess the risk of spill fires using thermal radiation hazard as the main reference, and a detailed framework for quantitative risk assessment of spill fires in ship engine room is established, which includes hazard identification, probability of failure calculation, consequence assessment, and risk quantification. The possible causes of spill fire accidents are briefly analyzed based on the bow-tie model. In cases where thermal threats above the risk threshold for larger leakage rates (70 mL/min), the probability method outperforms the threshold method in terms of accuracy in risk quantification. Additionally, the variation of thermal radiation with combustion diameter is analyzed, and some recommendations for fire emergency rescue are presented.

Energy and exergy-based degree-hours in estimation of heat requirements for heating and cooling purposes

This study presents an innovative exergy-based methodology to revolutionize the assessment of heating and cooling energy utilization, transcending the limitations of traditional heating and cooling degree-hours (HDH and CDH) analyses. The study’s distinctiveness stems from its investigation into variations in HDH and CDH concerning critical parameters such as ambient temperature, solar-air temperature, solar absorptivity, surface emissivity, and total heat transfer coefficient. This fosters a profound comprehension of the thermodynamic performance of building heating and cooling systems, empowering decision-makers with the insights needed to optimize energy utilization effectively. As demonstrated through a case study conducted in Antalya, Turkey, this study uncovers significant findings. A mere 1 °C increase in ambient temperature results in an average 14 % surge in heating demand and an average 17 % decline in cooling demand, leading to a substantial 1000°-h discrepancy between heating and cooling requirements. Furthermore, we underscore the sensitivity of energy demand to temperature fluctuations, the substantial impact of design temperature on energy consumption, the notable influence of solar effects on environmental conditions, and the potential for optimization in parameters such as solar absorptivity, surface emissivity, and total heat transfer coefficient. These insights underscore the significance of exergy-based systems, offering heightened energy efficiency, swift adaptability to temperature changes, integration of renewable energy sources, and intelligent control features that contribute to sustainability and energy savings.

The role of emissivity of the window surface inside and outside the atmospheric window in the radiative cooling effect

The emissivity design of building surfaces is crucial for radiative cooling (RC) heat dissipation. This work explores regularities of the influence of the emissivity inside and outside the atmospheric window (AW, 8-13 μm) on the window RC effect using a verified transient building heat transfer model. Results show that the RC effect brought by the radiant heat transfer of the window in non-atmospheric window bands (NAW) may exhibit a reversal phenomenon of first improvement and then weakening with the increase of the outer surface emissivity ε‾NAW. The occurrence of this reversal phenomenon is influenced by multiple factors such as meteorological parameters like ambient temperature and solar radiation, as well as architectural features including window orientation and window-to-wall ratio. In addition, as the window-to-wall ratio increases, when no reversal phenomenon occurs, the average RC regulation ability gap between the emissivity inside and outside the AW decreases from 7–40 times, which is observed when the reversal phenomenon occurs, to about 2–5 times, and the relative importance of ε‾NAW greatly increases. Regularities revealed provide more reliable guidance for the performance research and material design of RC windows.

ANALIZE NUMERICE DE CÂMP TERMIC ÎN MOTOARE ELECTRICE REDUNDANTE

In this paper, we propose to analyze the heat transfer of a torque motor with a limited angle under special space conditions. Three-dimensional models will be used, and two current values will be considered in numerical analysis. Variants in which the boundary conditions will consider different values of the emissivity of engine surfaces will also be considered. Inside the stator and rotor subassemblies of the motor, heat transfer will be carried out by conduction and radiation between the motor and the ambient environment. Using numerical analysis, it will be possible to determine the time during which the temperature in the winding reaches the maximum allowable value for the limited angle torque motor under the mentioned conditions.

Analytical Model of Optical-Field-Driven Subcycle Electron Tunneling Pulses from Two-Dimensional Materials.

We develop analytical models of optical-field-driven electron tunneling from the edge and surface of free-standing two-dimensional (2D) materials. We discover a universal scaling between the tunneling current density (J) and the electric field near the barrier (F): In(J/|F|β) ∝ 1/|F| with β values of 3/2 and 1 for edge emission and vertical surface emission, respectively. At ultrahigh values of F, the current density exhibits an unexpected high-field saturation effect due to the reduced dimensionality of the 2D material, which is absent in the traditional bulk material. Our calculation reveals the dc bias as an efficient method for modulating the optical-field tunneling subcycle emission characteristics. Importantly, our model is in excellent agreement with a recent experiment on graphene. Our results offer a useful framework for understanding optical-field tunneling emission from 2D materials, which are helpful for the development of optoelectronics and emerging petahertz vacuum nanoelectronics.

Multi-scale remote sensing retrieval model for land surface emissivity and its impact on land surface temperature estimation

ABSTRACT As a fundamental parameter of the surface radiation process, land surface emissivity (LSE) is the most direct factor affecting the land surface temperature (LST) retrieval accuracy. Based on the measured data from 2017 to 2023, the characteristics of LSE changes were analysed, different timescale LSE retrieval models were developed, and the impact of LSE on pixel scale observational LST acquisition was evaluated by using unmanned aerial vehicle (UAV) remote sensing images. The results show that with changes in atmospheric environmental conditions, the LSE changes are relatively less pronounced at 3.99 µm and 4.02 µm in the mid-infrared band and at 10.8 µm and 11.8 µm in the thermal infrared band than in the other bands. At the timescale above day, the LSE is significant correlation with the normalized differential vegetation index (NDVI). Vegetation is the main parameter that dominates the LSE change under heterogeneous underlying surfaces. On a daily timescale, LSE exhibits typical diurnal variation characteristics, and the amplitude of diurnal variation is influenced mainly by shallow soil water and heat conditions. The developed LSE model based on Fengyun-4A (FY-4A) satellite remote-sensing data can effectively reproduce the daily variation characteristics of LST and avoid the ‘jumping’ phenomenon that may occur in the NDVI threshold method. The root-mean-square error (RMSE) between the retrieved LST and in situ data is reduced to 3.78°C, and the retrieval accuracy is better than that of the published LST product. When using UAVs to obtain pixel-scale LSTs, dry bare soil is more sensitive to LSE. When the LSE increases from 0.95 to 1.0, the average LST obtained by the UAV deviates by approximately 1.0°C. This study preliminarily provides some spatiotemporal variation patterns of LSE and lays a foundation for the later-modified LST retrieval algorithms.

PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations

Abstract. This article introduces PyRTlib, a new standalone Python package for non-scattering line-by-line microwave radiative transfer simulations. PyRTlib is a flexible and user-friendly tool for computing down- and upwelling brightness temperatures and related quantities (e.g., atmospheric absorption, optical depth, opacity, mean radiating temperature) written in Python, a language commonly used nowadays for scientific software development, especially by students and early-career scientists. PyRTlib allows for simulating observations from ground-based, airborne, and satellite microwave sensors in clear-sky and in cloudy conditions (under non-scattering Rayleigh approximation). The intention for PyRTlib is not to be a competitor to state-of-the-art atmospheric radiative transfer codes that excel in speed and/or versatility (e.g., ARTS, Atmospheric Radiative Transfer Simulator; RTTOV, Radiative Transfer for TOVS (Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder)). The intention is to provide an educational tool, completely written in Python, to readily simulate atmospheric microwave radiative transfer from a variety of input profiles, including predefined climatologies, global radiosonde archives, and model reanalysis. The paper presents quick examples for the built-in modules to access popular open data archives. The paper also presents examples for computing the simulated brightness temperature for different platforms (ground-based, airborne, and satellite), using various input profiles, showing how to easily modify other relevant parameters, such as the observing angle (zenith, nadir, slant), surface emissivity, and gas absorption model. PyRTlib can be easily embedded in other Python codes needing atmospheric microwave radiative transfer (e.g., surface emissivity models and retrievals). Despite its simplicity, PyRTlib can be readily used to produce present-day scientific results, as demonstrated by two examples showing (i) an absorption model comparison and validation with ground-based radiometric observations and (ii) uncertainty propagation of spectroscopic parameters through the radiative transfer calculations following a rigorous approach. To our knowledge, the uncertainty estimate is not provided by any other currently available microwave radiative transfer code, making PyRTlib unique for this aspect in the atmospheric microwave radiative transfer code scenario.

Plume mode instability enhanced by emitter surface poisoning in hollow cathode

The unstable plume mode of hollow cathodes should be avoided in practical applications because it severely degrades the overall cathode lifetime. In this study, we investigate the spot-plume transition and plasma stability characteristics of an unused segmented lanthanum hexaboride emitter. The expansion of the unstable plume mode region is observed during a discharge experiment. Subsequently, the segmented emitter is retrieved, the inner surface of the emitter is observed, and the work function on the surface is measured at room temperature. The emitter surface exhibits color variations with oxygen and carbon detection. The downstream edge shows the original purple color and almost no degradation in the work function. The high temperature in this region promotes the desorption of carbon and oxygen. In the spot mode, this region mainly contributes to thermionic electron emission; therefore, the discharge voltage in the spot mode does not change during the discharge experiment. Carbon or carbide is detected in the middle of the axial direction on the emitter surface, where the surface temperature is not sufficiently high to desorb carbon during discharge. Based on the surface analysis results, the dominant substance in the region where carbon is detected was lanthanum carbide. An increase in the work function is indicated in the region, which appears to increase the plasma instability. According to previous studies, an increase in the work function results in a rise in the potential in the emitter, and an increase in the electron temperature in the outside plume region induces the plasma instability. Further investigation is needed to understand the mechanism connecting the rise in the work function and the rise in the electron temperature in the plume region.

Variability in surface CO2 flux: Implication for monitoring surface emission from geothermal fields

In the last decade the international push for the development of various renewable energy and the increase of the carbon tax for emitters, has put high enthalpy geothermal on a hot seat. Anthropic geothermal emissions in volcanic areas are not negligible due to the inherent nature of their volcanic setting but are counted regardless, similarly to a gas or coal power plant, despite their non-fossil carbon origin. Natural volcanic emissions are however poorly constrained due to the lack of field scale soil CO2 flux assessments. In this study, we analyse the temporal and spatial variations of soil CO2 flux and soil temperature in the Taupō region, Taupō Volcanic Zone, New Zealand, in the light of seasonal variation, field utilisation, and seismicity. Fortnightly monitoring between 2019 and 2023 at 8 sites across the Tauhara and Wairakei geothermal fields provides insight into changes of seasonal variations and geothermal activities. To understand the broader distribution of natural degassing and to compare the CO2 flux over decades, we repeated the CO2 flux survey between 2019 and 2023 and compared to previous results at Karapiti, Wairakei geothermal field (2004, 2018), Ring of Fire, Tauhara geothermal field (2006), and Rotokawa geothermal field (2003, 2011). Similar emissions but a change in the spatial distribution at Tauhara geothermal field suggests that human surface development has affected permeability in the shallow subsurface. In contrast, a similar spatial distribution of flux, but higher emissions, at Karapiti, Wairakei indicates the recovery or modification of reservoir pressure. Finally, a decrease of total emission flux of the natural geothermal features at Rotokawa coincides with the decrease of CO2eq emissions at the power stations. This study showcases the complexity and uncertainties of natural CO2 emission calculations and provides recommendations for future monitoring studies.